• DocumentCode
    2005976
  • Title

    Remaining useful life prediction based on nonlinear state space model

  • Author

    Jianmin, Zhao ; Tianle, Feng

  • Author_Institution
    Mech. Eng. Coll., Shijiazhuang, China
  • fYear
    2011
  • fDate
    24-25 May 2011
  • Firstpage
    1
  • Lastpage
    5
  • Abstract
    This paper proposes a nonlinear state space model (SSM) to estimate the health degradation and predict the remaining useful life(RUL) of industry asset. Expectation Maximization (EM) algorithm and particle filtering (PF) are introduced to estimate SSM parameters. A case study is utilized to predict RUL of industry asset.
  • Keywords
    expectation-maximisation algorithm; gears; particle filtering (numerical methods); remaining life assessment; RUL prediction; SSM parameter estimation; expectation maximization algorithm; health degradation estimation; industry asset; nonlinear state space model; particle filtering; remaining useful life prediction; Estimation; prediction; remaining useful life; state space model;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Prognostics and System Health Management Conference (PHM-Shenzhen), 2011
  • Conference_Location
    Shenzhen
  • Print_ISBN
    978-1-4244-7951-1
  • Electronic_ISBN
    978-1-4244-7949-8
  • Type

    conf

  • DOI
    10.1109/PHM.2011.5939528
  • Filename
    5939528
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=2005976